2015 Training Course - Applied Nonparametric Econometrics

Event Date:

27 Jul, 2015 - 31 Jul, 2015

Location:

IFPRI - Dakar

Overview

This course will expose students to the current practice of applied nonparametric methods. These methods are designed to overcome misspecification issues that dominate applied economic research. Using nonparametric methods can shed light on new issues that were previously hidden due to ad hoc model specifications imposed in the analysis. This class will provide hands on instruction to students in state-of-the-art nonparametric methods designed specifically to assist students with empirical issues that arise in the application of these techniques. The basic concepts of smoothing will be covered, complemented with numerous examples and illustrations through the open source software R. This combination of class instruction and computer tutorials will assist students in developing a sound foundation to apply nonparametric methods in their own research agendas.

Participants of this course should leave with the ability to understand the nuances of nonparametric estimation and inference and the empirical implications that manifest. Further, participants should be able to successfully integrate their data into R and construct nonparametric estimates for their models, conduct inference and rigorously interpret these results to provide sound policy insights. All methods discussed will be accompanied with corresponding R code, data and documentation to the literature at large making it easy for participants to follow along in the class as well as a check once the class has ended and they are engaged in their own analysis.

Course Outline

Day 1:

Introduction to R using the basic linear regression model (all notes, data and examples will be provided)

The course level is appropriate for participants with a background in economics, statistics, mathematics, and/or public policy. A strong background in quantitative analysis is required. Basic knowledge of the statistical software R is desirable. A general fluency in the statistical/econometric lingo at the (post-) doctoral level (hopefully in a non-statistics/econometric discipline) is required. More speci fically, the Law of Large Numbers and the Central Limit Theorem should be understood.

Software Requirements

This course will heavily leverage implementation in R, a powerful statistical software package that is freely available. R possesses the facilities to implement an impressive array of nonparametric estimators and tests as well as to serve as an interface for data manipulation, making it an ideal choice when discussing the application of nonparametric methods. Moreover, R's real strength is that users can readily and easily construct their own estimators and tests so that canned approaches do not need to be relied on, allowing users to stand on their legs when conducting empirical research.

If you would like to practice using Stata before taking the proficiency test, please review the modules below. Information included covers Stata use for beginners, linear regressions, bivariate regressions, and panel data. You will need to know this information to successfully complete the test.

Real Data Nonparametric Applications

Every participant is allowed to submit one application, no later than 4 weeks before the course. A selection will be made from the submitted applications to discuss in detail in the class and to illustrate the practical pitfalls that are encountered with real data. Additionally, applications and data sets taken from published research will also be made available for the class to provides participants with a truly hands on approach to nonparametric econometrics.

Christopher F. Parmeter is an Associate Professor in the Economics Department at the School of Business Administration at the University of Miami. His area of expertise is in applied econometrics with special interests in semi- and nonparametric methods, benefit transfers, meta-analysis and efficiency analysis. Dr. Parmeter has coauthored 30 peer reviewed scientific articles in leading econometric and applied economics journals.

About AGRODEP

The African Growth and Development Policy Modeling Consortium aims to position African experts as leaders in the study of strategic development issues in Africa and the broader agricultural growth and policy debate. AGRODEP facilitates use of economic modeling tools, promotes access to data sources, provides training and research grants, and supports collaboration between African and international researchers.
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